1 citations · 1 across the 2 of their papers we have counts for
3 papers
hep-ph2025
Applying Normalizing Flows for spin correlations reconstruction in associated top-quark pair and dark matter production
E. Abasov, L. Dudko, E. Iudin +5
We apply a unified machine-learning framework based on Normalizing Flows (NFs) for the event-by-event reconstruction of invisible momenta and the subsequent evaluation of spin-sens…
hep-ph2024
Application of Kolmogorov-Arnold Networks in high energy physics
E. Abasov, P. Volkov, G. Vorotnikov +5
Kolmogorov-Arnold Networks represent a recent advancement in machine learning, with the potential to outperform traditional perceptron-based neural networks across various domains…
physics.data-an2021★ 1 cited
Application of Deep Learning Technique to an Analysis of Hard Scattering Processes at Colliders
Lev Dudko, Petr Volkov, Georgii Vorotnikov +1
Deep neural networks have rightfully won the place of one of the most accurate analysis tools in high energy physics. In this paper we will cover several methods of improving the p…